def fragment(name, object=None, origin=1, zoom=0, quiet=1, _self=cmd):
'''
DESCRIPTION
"fragment" retrieves a 3D structure from the fragment library,
which is currently pretty meager (just amino acids).
USAGE
fragment name
'''
r = DEFAULT_ERROR
try:
if object == None:
object = name
model = fragments.get(str(name))
la = len(model.atom)
if la and int(origin):
position = _self.get_position()
for c in range(0, 3):
mean_c = sum([a.coord[c] for a in model.atom]) / la
mean_c = position[c] - mean_c
for a in model.atom:
a.coord[c] += mean_c
r = _self.load_model(model,
str(object),
quiet=quiet,
zoom=zoom,
_self=_self)
except IOError:
raise pymol.CmdException("unable to load fragment '%s'." % name)
if _self._raising(r, _self): raise pymol.CmdException
return r
def fragment(name, object=None, origin=1, zoom=0, quiet=1, _self=cmd):
'''
DESCRIPTION
"fragment" retrieves a 3D structure from the fragment library,
which is currently pretty meager (just amino acids).
USAGE
fragment name
'''
r = DEFAULT_ERROR
try:
if object==None:
object=name
model = fragments.get(str(name))
la = len(model.atom)
if la and int(origin):
position = _self.get_position()
for c in range(0,3):
mean_c = sum([a.coord[c] for a in model.atom]) / la
mean_c = position[c] - mean_c
for a in model.atom:
a.coord[c] += mean_c
r = _self.load_model(model,str(object),quiet=quiet,zoom=zoom, _self=_self)
except IOError:
raise pymol.CmdException("unable to load fragment '%s'." % name)
if _self._raising(r,_self): raise pymol.CmdException
return r
def fragment(name, object=None, origin=1, zoom=0, quiet=1, _self=cmd):
'''
DESCRIPTION
"fragment" retrieves a 3D structure from the fragment library,
which is currently pretty meager (just amino acids).
USAGE
fragment name
'''
r = DEFAULT_ERROR
try:
save = _self.get_setting_legacy('auto_zoom')
if object == None:
object = name
model = fragments.get(str(name))
la = len(model.atom)
if la:
mean = map(lambda x, la=la: x / la, [
reduce(operator.__add__,
map(lambda a: a.coord[0], model.atom)),
reduce(operator.__add__,
map(lambda a: a.coord[1], model.atom)),
reduce(operator.__add__,
map(lambda a: a.coord[2], model.atom))
])
position = _self.get_position()
for c in range(0, 3):
mean[c] = position[c] - mean[c]
map(lambda a, x=mean[c], c=c: _self._adjust_coord(a, c, x),
model.atom)
mean = map(lambda x, la=la: x / la, [
reduce(operator.__add__,
map(lambda a: a.coord[0], model.atom)),
reduce(operator.__add__,
map(lambda a: a.coord[1], model.atom)),
reduce(operator.__add__,
map(lambda a: a.coord[2], model.atom))
])
r = _self.load_model(model, str(object), quiet=quiet, zoom=zoom)
except IOError:
print "Error: unable to load fragment '%s'." % name
except:
traceback.print_exc()
print "Error: unable to load fragment '%s'." % name
if _self._raising(r, _self): raise pymol.CmdException
return r
def fragment(name, object=None, origin=1, zoom=0, quiet=1, _self=cmd):
"""
DESCRIPTION
"fragment" retrieves a 3D structure from the fragment library,
which is currently pretty meager (just amino acids).
USAGE
fragment name
"""
r = DEFAULT_ERROR
try:
save = _self.get_setting_legacy("auto_zoom")
if object == None:
object = name
model = fragments.get(str(name))
la = len(model.atom)
if la:
mean = map(
lambda x, la=la: x / la,
[
reduce(operator.__add__, map(lambda a: a.coord[0], model.atom)),
reduce(operator.__add__, map(lambda a: a.coord[1], model.atom)),
reduce(operator.__add__, map(lambda a: a.coord[2], model.atom)),
],
)
position = _self.get_position()
for c in range(0, 3):
mean[c] = position[c] - mean[c]
map(lambda a, x=mean[c], c=c: _self._adjust_coord(a, c, x), model.atom)
mean = map(
lambda x, la=la: x / la,
[
reduce(operator.__add__, map(lambda a: a.coord[0], model.atom)),
reduce(operator.__add__, map(lambda a: a.coord[1], model.atom)),
reduce(operator.__add__, map(lambda a: a.coord[2], model.atom)),
],
)
r = _self.load_model(model, str(object), quiet=quiet, zoom=zoom)
except IOError:
print "Error: unable to load fragment '%s'." % name
except:
traceback.print_exc()
print "Error: unable to load fragment '%s'." % name
if _self._raising(r, _self):
raise pymol.CmdException
return r
def peptide_rebuild(name, selection='all', cycles=1000, state=1, quiet=1, *, _self=cmd):
'''
DESCRIPTION
Rebuild the peptide from selection. All atoms which are present in
selection will be kept fixed, while atoms missing in selection are
placed by sculpting.
USAGE
peptide_rebuild name [, selection [, cycles [, state ]]]
SEE ALSO
stub2ala, add_missing_atoms, peptide_rebuild_modeller
'''
from chempy import fragments, feedback, models
cycles, state, quiet = int(cycles), int(state), int(quiet)
# suppress feedback for model merging
feedback['actions'] = False
# work with named selection
namedsele = _self.get_unused_name('_')
_self.select(namedsele, '{} & present'.format(selection), 0)
identifiers = []
_self.iterate(namedsele + ' and polymer and guide and alt +A',
'identifiers.append([segi,chain,resi,resv,resn])', space=locals())
model = models.Indexed()
for (segi,chain,resi,resv,resn) in identifiers:
try:
fname = resn.lower() if resn != 'MSE' else 'met'
frag = fragments.get(fname)
except IOError:
print(' Warning: unknown residue: ' + resn)
continue
for a in frag.atom:
a.segi = segi
a.chain = chain
a.resi = resi
a.resi_number = resv
a.resn = resn
model.merge(frag)
if not quiet:
print(' Loading model...')
_self.load_model(model, name, 1, zoom=0)
if _self.get_setting_boolean('auto_remove_hydrogens'):
_self.remove(name + ' and hydro')
_self.protect(name + ' in ' + namedsele)
_self.sculpt_activate(name)
_self.update(name, namedsele, 1, state)
_self.delete(namedsele)
if not quiet:
print(' Sculpting...')
_self.set('sculpt_field_mask', 0x003, name) # bonds and angles only
_self.sculpt_iterate(name, 1, int(cycles / 4))
_self.set('sculpt_field_mask', 0x09F, name) # local + torsions
_self.sculpt_iterate(name, 1, int(cycles / 4))
_self.set('sculpt_field_mask', 0x0FF, name) # ... + vdw
_self.sculpt_iterate(name, 1, int(cycles / 2))
_self.sculpt_deactivate(name)
_self.deprotect(name)
_self.unset('sculpt_field_mask', name)
if not quiet:
print(' Connecting peptide...')
pairs = _self.find_pairs(name + ' and name C', name + ' and name N', 1, 1, 2.0)
for pair in pairs:
_self.bond(*pair)
_self.h_fix(name)
if not quiet:
print(' peptide_rebuild: done')
def add_missing_atoms(selection='all', cycles=200, quiet=1, *, _self=cmd):
'''
DESCRIPTION
Mutate those residues to themselves which have missing atoms
SEE ALSO
stub2ala
'''
from collections import defaultdict
from chempy import fragments
cycles, quiet = int(cycles), int(quiet)
reference = {
'ALA': set(['CB']),
'ARG': set(['CB', 'CG', 'NE', 'CZ', 'NH1', 'NH2', 'CD']),
'ASN': set(['CB', 'CG', 'OD1', 'ND2']),
'ASP': set(['CB', 'CG', 'OD1', 'OD2']),
'CYS': set(['CB', 'SG']),
'GLN': set(['CB', 'CG', 'CD', 'NE2', 'OE1']),
'GLU': set(['CB', 'CG', 'OE2', 'CD', 'OE1']),
'GLY': set([]),
'HIS': set(['CE1', 'CB', 'CG', 'CD2', 'ND1', 'NE2']),
'ILE': set(['CB', 'CD1', 'CG1', 'CG2']),
'LEU': set(['CB', 'CG', 'CD1', 'CD2']),
'LYS': set(['CB', 'CG', 'NZ', 'CE', 'CD']),
'MET': set(['CB', 'CG', 'CE', 'SD']),
'PHE': set(['CE1', 'CB', 'CG', 'CZ', 'CD1', 'CD2', 'CE2']),
'PRO': set(['CB', 'CG', 'CD']),
'SER': set(['OG', 'CB']),
'THR': set(['CB', 'OG1', 'CG2']),
'TRP': set(['CZ2', 'CB', 'CG', 'CH2', 'CE3', 'CD1', 'CD2', 'CZ3', 'NE1', 'CE2']),
'TYR': set(['CE1', 'OH', 'CB', 'CG', 'CZ', 'CD1', 'CD2', 'CE2']),
'VAL': set(['CB', 'CG1', 'CG2']),
}
namedsele = _self.get_unused_name('_')
_self.select(namedsele, selection, 0)
namelists = defaultdict(list)
_self.iterate('(%s) and polymer' % namedsele,
'namelists[model,segi,chain,resn,resi,resv].append(name)',
space=locals())
sele_dict = defaultdict(list)
tmp_name = _self.get_unused_name('_')
for key, namelist in namelists.items():
resn = key[3]
if resn not in reference:
if not quiet:
print(' Unknown residue: + ' + resn)
continue
if not reference[resn].issubset(namelist):
try:
frag = fragments.get(resn.lower())
for a in frag.atom:
a.segi = key[1]
a.chain = key[2]
a.resi = key[4]
a.resi_number = key[5]
_self.load_model(frag, tmp_name, 1, zoom=0)
skey = '/%s/%s/%s/%s`%s' % key[:5]
_self.remove(skey + ' and not name N+C+O+OXT+CA')
_self.align(tmp_name, skey + ' and name N+C+CA', cycles=0)
_self.remove(tmp_name + ' and (name N+C+O+CA or hydro)')
_self.fuse('name CB and ' + tmp_name, 'name CA and ' + skey, move=0)
if resn == 'PRO':
_self.bond(skey + '/N', skey + '/CD')
_self.unpick()
_self.delete(tmp_name)
sele_dict[key[0]].append(skey)
if not quiet:
print(' Mutated ' + skey)
except:
print(' Mutating ' + skey + ' failed')
for model in sele_dict:
_self.sort(model)
sculpt_relax(' '.join(sele_dict[model]), 0, 0, model, cycles)
_self.delete(namedsele)
def peptide_rebuild(name, selection='all', cycles=1000, state=1, quiet=1):
'''
DESCRIPTION
Rebuild the peptide from selection. All atoms which are present in
selection will be kept fixed, while atoms missing in selection are
placed by sculpting.
USAGE
peptide_rebuild name [, selection [, cycles [, state ]]]
SEE ALSO
stub2ala, add_missing_atoms, peptide_rebuild_modeller
'''
from chempy import fragments, feedback, models
cycles, state, quiet = int(cycles), int(state), int(quiet)
# suppress feedback for model merging
feedback['actions'] = False
# work with named selection
namedsele = cmd.get_unused_name('_')
cmd.select(namedsele, selection, 0)
identifiers = []
cmd.iterate(namedsele + ' and polymer and guide and alt +A',
'identifiers.append([segi,chain,resi,resv,resn])', space=locals())
model = models.Indexed()
for (segi,chain,resi,resv,resn) in identifiers:
try:
fname = resn.lower() if resn != 'MSE' else 'met'
frag = fragments.get(fname)
except IOError:
print(' Warning: unknown residue:', resn)
continue
for a in frag.atom:
a.segi = segi
a.chain = chain
a.resi = resi
a.resi_number = resv
a.resn = resn
model.merge(frag)
if not quiet:
print(' Loading model...')
cmd.load_model(model, name, 1, zoom=0)
if cmd.get_setting_boolean('auto_remove_hydrogens'):
cmd.remove(name + ' and hydro')
cmd.protect(name + ' in ' + namedsele)
cmd.sculpt_activate(name)
cmd.update(name, namedsele, 1, state)
cmd.delete(namedsele)
if not quiet:
print(' Sculpting...')
cmd.set('sculpt_field_mask', 0x003, name) # bonds and angles only
cmd.sculpt_iterate(name, 1, int(cycles / 4))
cmd.set('sculpt_field_mask', 0x09F, name) # local + torsions
cmd.sculpt_iterate(name, 1, int(cycles / 4))
cmd.set('sculpt_field_mask', 0x0FF, name) # ... + vdw
cmd.sculpt_iterate(name, 1, int(cycles / 2))
cmd.sculpt_deactivate(name)
cmd.deprotect(name)
cmd.unset('sculpt_field_mask', name)
if not quiet:
print(' Connecting peptide...')
pairs = cmd.find_pairs(name + ' and name C', name + ' and name N', 1, 1, 2.0)
for pair in pairs:
cmd.bond(*pair)
cmd.h_fix(name)
if not quiet:
print(' peptide_rebuild: done')
def add_missing_atoms(selection='all', cycles=200, quiet=1):
'''
DESCRIPTION
Mutate those residues to themselves which have missing atoms
SEE ALSO
stub2ala
'''
from collections import defaultdict
from chempy import fragments
cycles, quiet = int(cycles), int(quiet)
reference = {
'ALA': set(['CB']),
'ARG': set(['CB', 'CG', 'NE', 'CZ', 'NH1', 'NH2', 'CD']),
'ASN': set(['CB', 'CG', 'OD1', 'ND2']),
'ASP': set(['CB', 'CG', 'OD1', 'OD2']),
'CYS': set(['CB', 'SG']),
'GLN': set(['CB', 'CG', 'CD', 'NE2', 'OE1']),
'GLU': set(['CB', 'CG', 'OE2', 'CD', 'OE1']),
'GLY': set([]),
'HIS': set(['CE1', 'CB', 'CG', 'CD2', 'ND1', 'NE2']),
'ILE': set(['CB', 'CD1', 'CG1', 'CG2']),
'LEU': set(['CB', 'CG', 'CD1', 'CD2']),
'LYS': set(['CB', 'CG', 'NZ', 'CE', 'CD']),
'MET': set(['CB', 'CG', 'CE', 'SD']),
'PHE': set(['CE1', 'CB', 'CG', 'CZ', 'CD1', 'CD2', 'CE2']),
'PRO': set(['CB', 'CG', 'CD']),
'SER': set(['OG', 'CB']),
'THR': set(['CB', 'OG1', 'CG2']),
'TRP': set(['CZ2', 'CB', 'CG', 'CH2', 'CE3', 'CD1', 'CD2', 'CZ3', 'NE1', 'CE2']),
'TYR': set(['CE1', 'OH', 'CB', 'CG', 'CZ', 'CD1', 'CD2', 'CE2']),
'VAL': set(['CB', 'CG1', 'CG2']),
}
namedsele = cmd.get_unused_name('_')
cmd.select(namedsele, selection, 0)
namelists = defaultdict(list)
cmd.iterate('(%s) and polymer' % namedsele,
'namelists[model,segi,chain,resn,resi,resv].append(name)',
space=locals())
sele_dict = defaultdict(list)
tmp_name = cmd.get_unused_name('_')
for key, namelist in namelists.items():
resn = key[3]
if resn not in reference:
if not quiet:
print(' Unknown residue:', resn)
continue
if not reference[resn].issubset(namelist):
try:
frag = fragments.get(resn.lower())
for a in frag.atom:
a.segi = key[1]
a.chain = key[2]
a.resi = key[4]
a.resi_number = key[5]
cmd.load_model(frag, tmp_name, 1, zoom=0)
skey = '/%s/%s/%s/%s`%s' % key[:5]
cmd.remove(skey + ' and not name N+C+O+OXT+CA')
cmd.align(tmp_name, skey + ' and name N+C+CA', cycles=0)
cmd.remove(tmp_name + ' and (name N+C+O+CA or hydro)')
cmd.fuse('name CB and ' + tmp_name, 'name CA and ' + skey, move=0)
if resn == 'PRO':
cmd.bond(skey + '/N', skey + '/CD')
cmd.unpick()
cmd.delete(tmp_name)
sele_dict[key[0]].append(skey)
if not quiet:
print(' Mutated ', skey)
except:
print(' Mutating', skey, 'failed')
for model in sele_dict:
cmd.sort(model)
sculpt_relax(' '.join(sele_dict[model]), 0, 0, model, cycles)
cmd.delete(namedsele)
